skip to main content


The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 11:00 PM ET on Friday, July 12 until 9:00 AM ET on Saturday, July 13 due to maintenance. We apologize for the inconvenience.

Title: Joint computational design of workspaces and workplans
Humans assume different production roles in a workspace. On one hand, humans design workplans to complete tasks as efficiently as possible in order to improve productivity. On the other hand, a nice workspace is essential to facilitate teamwork. In this way, workspace design and workplan design complement each other. Inspired by such observations, we propose an automatic approach to jointly design a workspace and a workplan. Taking staff properties, a space, and work equipment as input, our approach jointly optimizes a workspace and a workplan, considering performance factors such as time efficiency and congestion avoidance, as well as workload factors such as walk effort, turn effort, and workload balances. To enable exploration of design trade-offs, our approach generates a set of Pareto-optimal design solutions with strengths on different objectives, which can be adopted for different work scenarios. We apply our approach to synthesize workspaces and workplans for different workplaces such as a fast food kitchen and a supermarket. We also extend our approach to incorporate other common work considerations such as dynamic work demands and accommodating staff members with different physical capabilities. Evaluation experiments with simulations validate the efficacy of our approach for synthesizing effective workspaces and workplans.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
ACM Transactions on Graphics
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Ghate, A ; Krishnaiyer, K. ; Paynabar, K. (Ed.)
    Maintaining an appropriate staffing level is essential to providing a healthy workplace environment at nursing homes and ensuring quality care among residents. With the widespread Covid-19 pandemic, staff absenteeism frequently occurs due to mandatory quarantine and providing care to their inflicted family members. Even though some of the staff show up for work, they may have to perform additional pandemic-related protection duties. In combination, these changes lead to an uncertain reduction in the quantity of care each staff member able to provide in a future shift. To alleviate the staff shortage concern and maintain the necessary care quantity, we study the optimal shift scheduling problem for a skilled nursing facility under probabilistic staff shortage in the presence of pandemic-related service provision disruptions. We apply a two-stage stochastic programming approach to our study. Our objective is to assign staff (i.e., certified nursing aids) to shifts to minimize the total staffing cost associated with contract staff workload, the adjusted workload for the changing resident demand, and extra workload due to required sanitization. Thus, the uncertainties considered arise from probabilistic staff shortage in addition to resident service need fluctuation. We model the former source of uncertainty with a geometric random variable for each staffer. In a proof-of-the-concept study, we consider realistic COVID-19 pandemic response measures recommended by the Indiana state government. We extract payment parameter estimates from the COVID-19 Nursing Home Dataset publicly available by the Centers for Medicare and Medicaid Services (CMS). We conclude with our numerical experiments that when a skilled nursing facility is at low risk of the pandemic, the absenteeism rate and staff workload increase slightly, thus maintaining the current staffing level can still handle the service disruptions. On the other hand, under high-risk circumstances, with the sharp increase of the absence rate and workload, a care facility likely needs to hire additional full-time staff as soon as possible. Our research offers insights into staff shift scheduling in the face of uncertain staff shortages and service disruption due to pandemics and prolonged disasters. 
    more » « less
  2. Abstract Humans exhibit remarkably complex cognitive abilities and adaptive behavior in daily life. Cognitive operation in the " mental workspace, " such as mentally rotating a piece of luggage to fit into fixed trunk space, helps us maintain and manipulate information on a moment-to-moment basis. Skill acquisition in the " sensorimotor workspace, " such as learning a new mapping between the magnitude of new vehicle movement and wheel turn, allows us to adjust our behavior to changing environmental or internal demands to maintain appropriate motor performance. While this cognitive and sensorimotor synergy is at the root of adaptive behavior in the real world, their interplay has been understudied due to a divide-and-conquer approach. We evaluated whether a separate domain-specific or common domain-general operation drives mental and sensorimotor rotational transformations. We observed that participants improved the efficiency of mental rotation speed after the visuomotor rotation training, and their learning rate for visuomotor adaptation also improved after their mental rotation training. Such bidirectional transfer between two widely different tasks highlights the remarkable reciprocal plasticity and demonstrates a common transformation mechanism between two intertwined workspaces. Our findings urge the necessity of an explicitly integrated approach to enhance our understanding of the dynamic interdependence between cognitive and sensorimotor mechanisms. 
    more » « less
  3. We explore Spatial Augmented Reality (SAR) precues (predictive cues) for procedural tasks within and between workspaces and for visualizing multiple upcoming steps in advance. We designed precues based on several factors: cue type, color transparency, and multi-level (number of precues). Precues were evaluated in a procedural task requiring the user to press buttons in three surrounding workspaces. Participants performed fastest in conditions where tasks were linked with line cues with different levels of color transparency. Precue performance was also affected by whether the next task was in the same workspace or a different one. 
    more » « less
  4. This paper explores the tradeoffs between different types of mixed reality robotic communication under different levels of user workload. We present the results of a within-subjects experiment in which we systematically and jointly vary robot communication style alongside level and type of cognitive load, and measure subsequent impacts on accuracy, reaction time, and perceived workload and effectiveness. Our preliminary results suggest that although humans may not notice differences, the manner of load a user is under and the type of communication style used by a robot they interact with do in fact interact to determine their task effectiveness 
    more » « less
  5. null (Ed.)
    Triangle enumeration is a fundamental problem in large-scale graph analysis. For instance, triangles are used to solve practical problems like community detection and spam filtering. On the other hand, there is a large amount of data stored on database management systems (DBMSs), which can be modeled and analyzed as graphs. Alternatively, graph data can be quickly loaded into a DBMS. Our paper shows how to adapt and optimize a randomized distributed triangle enumeration algorithm with SQL queries, which is a significantly different approach from programming graph algorithms in traditional languages such as Python or C++. We choose a parallel columnar DBMS given its fast query processing, but our solution should work for a row DBMS as well. Our randomized solution provides a balanced workload for parallel query processing, being robust to the existence of skewed degree vertices. We experimentally prove our solution ensures a balanced data distribution, and hence workload, among machines. The key idea behind the algorithm is to evenly partition all possible triplets of vertices among machines, sending edges that may form a triangle to a proxy machine; this edge redistribution eliminates shuffling edges during join computation and therefore triangle enumeration becomes local and fully parallel. In summary, our algorithm exhibits linear speedup with large graphs, including graphs that have high skewness in vertex degree distributions. 
    more » « less